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首页> 外文期刊>International Journal of Robust and Nonlinear Control >Eco-driving in urban traffic networks using traffic signals information
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Eco-driving in urban traffic networks using traffic signals information

机译：利用交通信号信息在城市交通网络中进行生态驾驶

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摘要

The problem of eco-driving is analyzed for an urban traffic network in presence of signalized intersections. It is assumed that the traffic light timings are known and available to the vehicles via infrastructure-to-vehicle communication. This work provides a solution to the energy consumption minimization while traveling through a sequence of signalized intersections and always catching a green light. The optimal- control problem is non-convex because of the constraints coming from the traffic lights; therefore, a sub-optimal strategy to restore the convexity and solve the problem is proposed. Firstly, a pruning algorithm aims at reducing the optimization domain by considering only the portions of the traffic light's green phases that allow to drive in compliance with the city speed limits. Then, a graph is created in the feasible region in order to approximate the energy consumption associated with each available path in the driving horizon. Lastly, after the problem convexity is recovered, a simple optimization problem is solved on the selected path to calculate the optimal crossing times at each intersection. The optimal speeds are then suggested to the driver. The proposed sub-optimal strategy is compared with the optimal solution provided by dynamic programming for validation purposes. It is also shown that the low computational load of the presented approach enables robustness properties and results very appealing for online use. Copyright (c) 2015 John Wiley & Sons, Ltd.
机译：针对存在信号交叉口的城市交通网络，分析了生态驾驶问题。假设通过基础设施到车辆的通信，交通信号灯的定时是已知的并且对车辆可用。这项工作为在通过一系列信号交叉口并始终捕获绿灯时最小化能耗提供了解决方案。由于交通信号灯的限制，最优控制问题是非凸的。因此，提出了一种恢复凸度并解决问题的次优策略。首先，修剪算法旨在通过仅考虑交通信号灯绿相中允许遵守城市限速行驶的部分来减少优化范围。然后，在可行区域中创建一个图表，以便估算与驾驶视野中每个可用路径相关的能耗。最后，在恢复问题凸度之后，对所选路径求解一个简单的优化问题，以计算每个交叉点的最佳交叉时间。然后将最佳速度建议给驾驶员。将所提出的次优策略与动态编程提供的最优解决方案进行比较，以进行验证。还表明，所提出的方法的低计算负荷使得鲁棒性和结果对于在线使用非常有吸引力。版权所有（c）2015 John Wiley＆Sons，Ltd.

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